Displaying videos based upon selectable inputs associated with tags

ABSTRACT

One or more computing devices, systems, and/or methods for displaying videos based upon selectable inputs associated with tags are presented. For example, a video may be identified. A transcript, associated with the video, may be determined. The transcript may comprise a plurality of text segments. The transcript may be analyzed to generate a plurality of sets of tags associated with the transcript. A plurality of selectable inputs may be generated based upon the plurality of sets of tags. A video interface, comprising the plurality of selectable inputs, may be displayed on a first device. A selection of a first selectable input may be received via the video interface. The first selectable input may be associated with a first tag of the plurality of sets of tags and a first time of the video. A second device may display the video based upon the first time of the video.

BACKGROUND

Many services, such as websites, applications, etc. may provideplatforms for viewing media, such as videos. For example, a user mayinteract with a service. A list of videos may be presented to the userwhile interacting with the service. The user may be interested in(viewing) a video of the list of videos. However, the user may (merely)be interested in viewing a segment of the video associated with one ormore subjects that the user is interested in. It may be difficult and/orit may take a substantial amount of time for the user to determine whichportion of the video comprises the segment associated with the one ormore subjects.

SUMMARY

In accordance with the present disclosure, one or more computing devicesand/or methods are provided. In an example, a video (e.g., a newschannel video clip, an educational video clip, etc.) may be identified.The video may comprise video data (e.g., a visual component of thevideo) and audio data (e.g., an audio component of the video). Atranscript associated with the audio data may be determined. Thetranscript may comprise a plurality of text segments. Each text segmentmay be associated with a time segment of a duration of time of thevideo. The transcript may be analyzed to generate a plurality of sets oftags (e.g., President, Politics, etc.) associated with the transcript.Each set of tags of the plurality of sets of tags may correspond to atext segment of the plurality of text segments. A plurality ofselectable inputs (e.g., electronic buttons, selectable graphicalobjects, selectable text objects, etc.) may be generated based upon theplurality of sets of tags. Each selectable input of the plurality ofselectable inputs may correspond to an indication of a tag of theplurality of sets of tags and a time associated with the tag. A firstgraphical user interface of a first client device may be controlled todisplay a video interface comprising the plurality of selectable inputs.A selection of a first selectable input of the plurality of selectableinputs may be received via the video interface. The first selectableinput may be associated with a first tag of the plurality of sets oftags and a first time of the video. Responsive to receiving theselection of the first selectable input, a second graphical userinterface of a second client device may be controlled to display thevideo. The video may be displayed based upon the first time of thevideo.

In an example, a plurality of selectable inputs may be generated basedupon a plurality of sets of tags associated with a video. Eachselectable input of the plurality of selectable inputs may correspond toan indication of a tag of the plurality of sets of tags and a timeassociated with the tag. A first graphical user interface of a firstclient device may be controlled to display a video interface comprisingthe plurality of selectable inputs. A selection of a first selectableinput of the plurality of selectable inputs may be received via thevideo interface. The first selectable input may be associated with afirst tag of the plurality of sets of tags and a first time of thevideo. Responsive to receiving the selection of the first selectableinput, a second graphical user interface of a second client device maybe controlled to display the video. The video may be displayed basedupon the first time of the video.

In an example, a video may be identified. The video may comprise videodata and audio data. A transcript associated with the audio data may bedetermined. The transcript may comprise a plurality of text segments.Each text segment may be associated with a time segment of a duration oftime of the video. The transcript may be analyzed to generate aplurality of sets of tags associated with the transcript. Each set oftags of the plurality of sets of tags may correspond to a text segmentof the plurality of text segments. A plurality of selectable inputs maybe generated based upon the plurality of sets of tags. Each selectableinput of the plurality of selectable inputs may correspond to anindication of a tag of the plurality of sets of tags and a timeassociated with the tag.

DESCRIPTION OF THE DRAWINGS

While the techniques presented herein may be embodied in alternativeforms, the particular embodiments illustrated in the drawings are only afew examples that are supplemental of the description provided herein.These embodiments are not to be interpreted in a limiting manner, suchas limiting the claims appended hereto.

FIG. 1 is an illustration of a scenario involving various examples ofnetworks that may connect servers and clients.

FIG. 2 is an illustration of a scenario involving an exampleconfiguration of a server that may utilize and/or implement at least aportion of the techniques presented herein.

FIG. 3 is an illustration of a scenario involving an exampleconfiguration of a client that may utilize and/or implement at least aportion of the techniques presented herein.

FIG. 4 is a flow chart illustrating an example method for displayingvideos based upon selectable inputs associated with tags.

FIG. 5A is a component block diagram illustrating an example system fordisplaying videos based upon selectable inputs associated with tags,where a first graphical user interface of a first device is controlledto display a video interface.

FIG. 5B is a component block diagram illustrating an example system fordisplaying videos based upon selectable inputs associated with tags,where a backend system generates a plurality of selectable inputsresponsive to a first video being uploaded to one or more servers and/orto a video database.

FIG. 5C is a component block diagram illustrating an example system fordisplaying videos based upon selectable inputs associated with tags,where a second graphical user interface of a second device is controlledto display a video interface comprising a list of video items.

FIG. 5D is a component block diagram illustrating an example system fordisplaying videos based upon selectable inputs associated with tags,where a second graphical user interface of a second device is controlledto display a first video and/or a plurality of selectable inputs.

FIG. 5E is a component block diagram illustrating an example system fordisplaying videos based upon selectable inputs associated with tags,where a second graphical user interface of a second device is controlledto display a first video based upon a third time of the first video.

FIG. 6 is an illustration of a scenario featuring an examplenon-transitory machine readable medium in accordance with one or more ofthe provisions set forth herein.

DETAILED DESCRIPTION

Subject matter will now be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, specific example embodiments. Thisdescription is not intended as an extensive or detailed discussion ofknown concepts. Details that are known generally to those of ordinaryskill in the relevant art may have been omitted, or may be handled insummary fashion.

The following subject matter may be embodied in a variety of differentforms, such as methods, devices, components, and/or systems.Accordingly, this subject matter is not intended to be construed aslimited to any example embodiments set forth herein. Rather, exampleembodiments are provided merely to be illustrative. Such embodimentsmay, for example, take the form of hardware, software, firmware or anycombination thereof.

1. Computing Scenario

The following provides a discussion of some types of computing scenariosin which the disclosed subject matter may be utilized and/orimplemented.

1.1. Networking

FIG. 1 is an interaction diagram of a scenario 100 illustrating aservice 102 provided by a set of servers 104 to a set of client devices110 via various types of networks. The servers 104 and/or client devices110 may be capable of transmitting, receiving, processing, and/orstoring many types of signals, such as in memory as physical memorystates.

The servers 104 of the service 102 may be internally connected via alocal area network 106 (LAN), such as a wired network where networkadapters on the respective servers 104 are interconnected via cables(e.g., coaxial and/or fiber optic cabling), and may be connected invarious topologies (e.g., buses, token rings, meshes, and/or trees). Theservers 104 may be interconnected directly, or through one or more othernetworking devices, such as routers, switches, and/or repeaters. Theservers 104 may utilize a variety of physical networking protocols(e.g., Ethernet and/or Fiber Channel) and/or logical networkingprotocols (e.g., variants of an Internet Protocol (IP), a TransmissionControl Protocol (TCP), and/or a User Datagram Protocol (UDP). The localarea network 106 may include, e.g., analog telephone lines, such as atwisted wire pair, a coaxial cable, full or fractional digital linesincluding T1, T2, T3, or T4 type lines, Integrated Services DigitalNetworks (ISDNs), Digital Subscriber Lines (DSLs), wireless linksincluding satellite links, or other communication links or channels,such as may be known to those skilled in the art. The local area network106 may be organized according to one or more network architectures,such as server/client, peer-to-peer, and/or mesh architectures, and/or avariety of roles, such as administrative servers, authenticationservers, security monitor servers, data stores for objects such as filesand databases, business logic servers, time synchronization servers,and/or front-end servers providing a user-facing interface for theservice 102.

Likewise, the local area network 106 may comprise one or moresub-networks, such as may employ differing architectures, may becompliant or compatible with differing protocols and/or may interoperatewithin the local area network 106. Additionally, a variety of local areanetworks 106 may be interconnected; e.g., a router may provide a linkbetween otherwise separate and independent local area networks 106.

In the scenario 100 of FIG. 1, the local area network 106 of the service102 is connected to a wide area network 108 (WAN) that allows theservice 102 to exchange data with other services 102 and/or clientdevices 110. The wide area network 108 may encompass variouscombinations of devices with varying levels of distribution andexposure, such as a public wide-area network (e.g., the Internet) and/ora private network (e.g., a virtual private network (VPN) of adistributed enterprise).

In the scenario 100 of FIG. 1, the service 102 may be accessed via thewide area network 108 by a user 112 of one or more client devices 110,such as a portable media player (e.g., an electronic text reader, anaudio device, or a portable gaming, exercise, or navigation device); aportable communication device (e.g., a camera, a phone, a wearable or atext chatting device); a workstation; and/or a laptop form factorcomputer. The respective client devices 110 may communicate with theservice 102 via various connections to the wide area network 108. As afirst such example, one or more client devices 110 may comprise acellular communicator and may communicate with the service 102 byconnecting to the wide area network 108 via a wireless local areanetwork 106 provided by a cellular provider. As a second such example,one or more client devices 110 may communicate with the service 102 byconnecting to the wide area network 108 via a wireless local areanetwork 106 provided by a location such as the user's home or workplace(e.g., a WiFi (Institute of Electrical and Electronics Engineers (IEEE)Standard 802.11) network or a Bluetooth (IEEE Standard 802.15.1)personal area network). In this manner, the servers 104 and the clientdevices 110 may communicate over various types of networks. Other typesof networks that may be accessed by the servers 104 and/or clientdevices 110 include mass storage, such as network attached storage(NAS), a storage area network (SAN), or other forms of computer ormachine readable media.

1.2. Server Configuration

FIG. 2 presents a schematic architecture diagram 200 of a server 104that may utilize at least a portion of the techniques provided herein.Such a server 104 may vary widely in configuration or capabilities,alone or in conjunction with other servers, in order to provide aservice such as the service 102.

The server 104 may comprise one or more processors 210 that processinstructions. The one or more processors 210 may optionally include aplurality of cores; one or more coprocessors, such as a mathematicscoprocessor or an integrated graphical processing unit (GPU); and/or oneor more layers of local cache memory. The server 104 may comprise memory202 storing various forms of applications, such as an operating system204; one or more server applications 206, such as a hypertext transportprotocol (HTTP) server, a file transfer protocol (FTP) server, or asimple mail transport protocol (SMTP) server; and/or various forms ofdata, such as a database 208 or a file system. The server 104 maycomprise a variety of peripheral components, such as a wired and/orwireless network adapter 214 connectible to a local area network and/orwide area network; one or more storage components 216, such as a harddisk drive, a solid-state storage device (SSD), a flash memory device,and/or a magnetic and/or optical disk reader.

The server 104 may comprise a mainboard featuring one or morecommunication buses 212 that interconnect the processor 210, the memory202, and various peripherals, using a variety of bus technologies, suchas a variant of a serial or parallel AT Attachment (ATA) bus protocol; aUniform Serial Bus (USB) protocol; and/or Small Computer SystemInterface (SCI) bus protocol. In a multibus scenario, a communicationbus 212 may interconnect the server 104 with at least one other server.Other components that may optionally be included with the server 104(though not shown in the schematic diagram 200 of FIG. 2) include adisplay; a display adapter, such as a graphical processing unit (GPU);input peripherals, such as a keyboard and/or mouse; and a flash memorydevice that may store a basic input/output system (BIOS) routine thatfacilitates booting the server 104 to a state of readiness.

The server 104 may operate in various physical enclosures, such as adesktop or tower, and/or may be integrated with a display as an“all-in-one” device. The server 104 may be mounted horizontally and/orin a cabinet or rack, and/or may simply comprise an interconnected setof components. The server 104 may comprise a dedicated and/or sharedpower supply 218 that supplies and/or regulates power for the othercomponents. The server 104 may provide power to and/or receive powerfrom another server and/or other devices. The server 104 may comprise ashared and/or dedicated climate control unit 220 that regulates climateproperties, such as temperature, humidity, and/or airflow. Many suchservers 104 may be configured and/or adapted to utilize at least aportion of the techniques presented herein.

1.3. Client Device Configuration

FIG. 3 presents a schematic architecture diagram 300 of a client device110 whereupon at least a portion of the techniques presented herein maybe implemented. Such a client device 110 may vary widely inconfiguration or capabilities, in order to provide a variety offunctionality to a user such as the user 112. The client device 110 maybe provided in a variety of form factors, such as a desktop or towerworkstation; an “all-in-one” device integrated with a display 308; alaptop, tablet, convertible tablet, or palmtop device; a wearable devicemountable in a headset, eyeglass, earpiece, and/or wristwatch, and/orintegrated with an article of clothing; and/or a component of a piece offurniture, such as a tabletop, and/or of another device, such as avehicle or residence. The client device 110 may serve the user in avariety of roles, such as a workstation, kiosk, media player, gamingdevice, and/or appliance.

The client device 110 may comprise one or more processors 310 thatprocess instructions. The one or more processors 310 may optionallyinclude a plurality of cores; one or more coprocessors, such as amathematics coprocessor or an integrated graphical processing unit(GPU); and/or one or more layers of local cache memory. The clientdevice 110 may comprise memory 301 storing various forms ofapplications, such as an operating system 303; one or more userapplications 302, such as document applications, media applications,file and/or data access applications, communication applications such asweb browsers and/or email clients, utilities, and/or games; and/ordrivers for various peripherals. The client device 110 may comprise avariety of peripheral components, such as a wired and/or wirelessnetwork adapter 306 connectible to a local area network and/or wide areanetwork; one or more output components, such as a display 308 coupledwith a display adapter (optionally including a graphical processing unit(GPU)), a sound adapter coupled with a speaker, and/or a printer; inputdevices for receiving input from the user, such as a keyboard 311, amouse, a microphone, a camera, and/or a touch-sensitive component of thedisplay 308; and/or environmental sensors, such as a global positioningsystem (GPS) receiver 319 that detects the location, velocity, and/oracceleration of the client device 110, a compass, accelerometer, and/orgyroscope that detects a physical orientation of the client device 110.Other components that may optionally be included with the client device110 (though not shown in the schematic architecture diagram 300 of FIG.3) include one or more storage components, such as a hard disk drive, asolid-state storage device (SSD), a flash memory device, and/or amagnetic and/or optical disk reader; and/or a flash memory device thatmay store a basic input/output system (BIOS) routine that facilitatesbooting the client device 110 to a state of readiness; and a climatecontrol unit that regulates climate properties, such as temperature,humidity, and airflow.

The client device 110 may comprise a mainboard featuring one or morecommunication buses 312 that interconnect the processor 310, the memory301, and various peripherals, using a variety of bus technologies, suchas a variant of a serial or parallel AT Attachment (ATA) bus protocol;the Uniform Serial Bus (USB) protocol; and/or the Small Computer SystemInterface (SCI) bus protocol. The client device 110 may comprise adedicated and/or shared power supply 318 that supplies and/or regulatespower for other components, and/or a battery 304 that stores power foruse while the client device 110 is not connected to a power source viathe power supply 318. The client device 110 may provide power to and/orreceive power from other client devices.

In some scenarios, as a user 112 interacts with a software applicationon a client device 110 (e.g., an instant messenger and/or electronicmail application), descriptive content in the form of signals or storedphysical states within memory (e.g., an email address, instant messengeridentifier, phone number, postal address, message content, date, and/ortime) may be identified. Descriptive content may be stored, typicallyalong with contextual content. For example, the source of a phone number(e.g., a communication received from another user via an instantmessenger application) may be stored as contextual content associatedwith the phone number. Contextual content, therefore, may identifycircumstances surrounding receipt of a phone number (e.g., the date ortime that the phone number was received), and may be associated withdescriptive content. Contextual content, may, for example, be used tosubsequently search for associated descriptive content. For example, asearch for phone numbers received from specific individuals, receivedvia an instant messenger application or at a given date or time, may beinitiated. The client device 110 may include one or more servers thatmay locally serve the client device 110 and/or other client devices ofthe user 112 and/or other individuals. For example, a locally installedwebserver may provide web content in response to locally submitted webrequests. Many such client devices 110 may be configured and/or adaptedto utilize at least a portion of the techniques presented herein.

2. Presented Techniques

One or more computing devices, systems, and/or techniques for displayingvideos based upon selectable inputs associated with tags are presented.For example, a user (and/or a device associated with the user) mayaccess and/or interact with a service, such as a website, anapplication, etc. that provides a platform for viewing and/ordownloading videos from a server (of the website, the application,etc.). For example, the user may be interested in consuming a video(e.g., a news channel video clip, an educational video clip, etc.).However, the user may (merely) be interested in consuming one or moreportions of the video associated with one or more topics and/or one ormore entities (e.g., the user may have an interest in the one or moretopics and/or the one or more entities). It may be difficult and/or itmay take a substantial amount of time for the user to find the one ormore portions of the video (associated with the one or more topicsand/or the one or more entities). Accordingly, the user may be unable tofind the one or more portions of the video and/or the user may spend aconsiderable amount of time waiting for the one or more portions of thevideo and/or finding the one or more portions of the video (e.g., bymanually skipping through sections of the video).

Thus, in accordance with one or more of the techniques presented herein,a transcript associated with audio data of the video may be determined.The transcript may be analyzed to generate a plurality of sets of tags(e.g., President, Politics, etc.) associated with the transcript. Aplurality of selectable inputs (e.g., electronic buttons, selectablegraphical objects, selectable text objects, etc. representative ofPresident, Politics, etc.) may be generated based upon the plurality ofsets of tags. The plurality of selectable inputs may be displayed viathe device (associated with the user). A first selectable input of theplurality of selectable inputs (e.g., the first selectable input may beassociated with the one or more topics and/or the one or more entitiesthat the user is interested in) may be selected. Responsive to theselection of the first selectable input, the video may be displayedbased upon a first time of the video associated with the firstselectable input (e.g., the first time may be associated with the one ormore topics and/or the one or more entities that the user is interestedin).

An embodiment of displaying videos based upon selectable inputsassociated with tags is illustrated by an example method 400 of FIG. 4.A user, such as user Jill, and/or a device associated with the user) mayaccess and/or interact with a service, such as a website, anapplication, etc. that provides a platform for viewing and/ordownloading videos from a server (of the website, the application,etc.). For example, a graphical user interface of the device may becontrolled to display a video interface comprising a list of videos thatmay be accessed, viewed and/or downloaded via the video interface.

At 402, a first video may be identified. For example, the first videomay be identified from a video database associated with the service. Insome examples, the first video may be identified responsive to aselection of the first video (via the video interface) by one or moreusers (and/or one or more devices associated with the one or moreusers). Alternatively and/or additionally, the first video may beidentified responsive to receiving the first video. For example, thefirst video may be identified responsive to the first video beinguploaded to the video database (and/or being uploaded to one or moreservers associated with the service) by one or more users (and/or one ormore devices associated with the one or more users), an administrator,etc.

The video database may be stored in the one or more servers (associatedwith the service). The video database may comprise a data structurecorresponding to a plurality of videos. The data structure may comprisethe plurality of videos and/or a plurality of sets of information. Eachset of information of the plurality of sets of information maycorrespond to a video of the plurality of videos. Each set ofinformation of the plurality of sets of information may comprise a title(e.g., a name) of a video of the plurality of videos, an indication of aduration of time of the video, a description of subject matter of thevideo, a transcript of the video, etc.

In some examples, the first video may be a news-related video (e.g., anews channel video clip, an internet news video clip, etc.).Alternatively and/or additionally, the first video may be aninstructional video (e.g., a how-to video clip, an educational videoclip, etc.). Alternatively and/or additionally, the first video may bean interview-related video (e.g., a documentary video clip, a video clipof a meeting, etc.). Alternatively and/or additionally, the first videomay be a different type of video (e.g., a sports-related video clip, anentertainment-related video clip, etc.).

The first video may comprise video data (e.g., a visual component of thefirst video) and audio data (e.g., an audio component of the firstvideo). At 404, a transcript may be determined associated with the audiodata (of the first video). In some examples, the transcript may comprisetext representative of words and/or sounds of the audio data. In someexamples, the transcript may comprise a plurality of text segments. Eachtext segment of the plurality of text segments may be associated with atime segment of a duration of time of the first video. In some examples,the transcript may comprise a set of captions and/or a set of subtitlesassociated with the first video.

In some examples, each text segment of the plurality of text segmentsmay comprise one sentence of the audio data. Alternatively and/oradditionally, each text segment of the plurality of text segments maycomprise a plurality of sentences of the audio data. For example, thetranscript may be divided into the plurality of text segments based upona number of sentences (e.g., 1 sentence, 2 sentences, 3, sentences,etc.) (corresponding to each text segment of the plurality of textsegments).

Alternatively and/or additionally, each text segment of the plurality oftext segments may comprise words and/or sounds of the audio dataassociated with a second duration of time. For example, each textsegment of the plurality of text segments may be associated with a timesegment having the second duration of time. For example, the transcriptmay be divided into the plurality of text segments based upon the secondduration of time.

A first text segment may be representative of words and/or sounds of theaudio data during a first time segment of the duration of time of thefirst video. In some examples, the first text segment may comprise textrepresentative of the words and/or the sounds of the audio data duringthe first time segment. Alternatively and/or additionally, the firsttext segment may (merely) comprise text representative of the words ofthe audio data during the first time segment. For example, the firsttext segment may comprise: “The President made a big decision todayrelated to jobs”.

Alternatively and/or additionally, the first text segment may compriseone or more indications of the first time segment. For example, thefirst text segment may comprise: “00:00:03→00:00:11”, indicating thatthe first text segment corresponds to the words and/or the sounds of theaudio data from a first time of the first video (e.g., 00:00:03, 3seconds into the first video, etc.) to a second time of the first video(e.g., 00:00:11, 11 seconds into the first video, etc.). The first timeof the first video may correspond to a beginning of the first timesegment and/or the second time of the first video may correspond to anend of the first time segment. Alternatively and/or additionally, thefirst text segment may (merely) comprise the first time or the secondtime (rather than both the first time and the second time).

Alternatively and/or additionally, the first text segment may compriseone or more indications of a person and/or a title of the person thatspoke the words and/or the sounds of the audio data during the firsttime segment. For example, the first text segment may comprise:“Newscaster 1:”.

Alternatively and/or additionally, the first text segment may comprisethe one or more indications of the first time segment, the one or moreindications of the person and/or the title of the person that spoke thewords and/or the sounds of the audio data during the first time segment,and/or text representative of the words and/or the sounds of the audiodata during the first time segment. For example, the first text segmentmay comprise: “00:00:03→00:00:11 Newscaster 1: The President made a bigdecision today related to jobs”.

In some examples, the transcript may be retrieved from (the plurality ofsets of information of) the video database. Alternatively and/oradditionally, the first video may comprise the transcript (as part ofthe first video, embedded within the first video, etc.). Accordingly,the transcript may be retrieved from (within) the first video.

Alternatively and/or additionally, the transcript may not be available(in the video database and/or the first video). Accordingly, the audiodata of the first video may be transcribed to generate the transcript.For example, the first video may be transcribed (e.g., automatically) byusing speech recognition (e.g., automatic speech recognition) techniquesand/or other techniques. Alternatively and/or additionally, the firstvideo may be transcribed manually.

At 406, the transcript may be analyzed to generate a plurality of setsof tags associated with the transcript. For example, each set of tags ofthe plurality of sets of tags corresponds to a text segment of theplurality of text segments. For example, the plurality of sets of tagsmay comprise indications a plurality of sets of entities and/orindications of a plurality of sets of topics.

In some examples, the plurality of sets of entities (e.g., namedentities) may comprise subjects (expressed, discussed, etc.) in thefirst video. For example, the plurality of sets of entities may compriseplaces (e.g., countries, cities, geographic locations, etc.), people(e.g., people of a particular location, people with a particularoccupation, politicians, celebrities, socialites, etc.), things (e.g.,devices, natural objects, etc.), organizations, ideas, systems, events,historical events, current events, abstract objects, physical objects,etc.

In some examples, the transcript may be analyzed to identify theplurality of sets of entities. Each set of entities of the plurality ofsets of entities may correspond to a text segment of the plurality oftext segments. In some examples, the plurality of sets of entities maybe identified by comparing each text segment of the plurality of textsegments to one or more information databases. For example, textsegments of the plurality of text segments may be compared with one ormore first resources (e.g., an encyclopedia, an online encyclopedia, anews channel, a news website, a website, a book, a research article, aresearch article database and/or a different type of informationdatabase, etc.) to identify the plurality of sets of entities.Alternatively and/or additionally, the transcript may be analyzed usingone or more named-entity recognition (NER) techniques to identify theplurality of sets of entities.

In some examples, the plurality of sets of topics (e.g., labels) maycomprise topics (expressed, discussed, etc.) in the first video. In someexamples, the plurality of sets of topics may (each) be selected from alist of topics. In some examples, the list of topics may be based uponthe subject matter of the first video. In an example, the first videomay be a news-related video. Accordingly, the list of topics maycomprise: The Economy, Politics, Business News, The United States,International News, The White House, Entertainment, Celebrity News,Science News, Technology, Health News, etc. In a second example, thefirst video may be a travel-related video. Accordingly, the list oftopics may comprise: Travel destinations, Cuisine, Transportation,Cost-friendliness, Asia Tourism, South America Tourism, Africa Tourism,etc.

In some examples, the transcript may be analyzed to identify theplurality of sets of topics. Each set of topics of the plurality of setsof topics may correspond to a text segment of the plurality of textsegments. In some examples, the plurality of sets of topics may beidentified by comparing each text segment of the plurality of textsegments to one or more information databases. For example, textsegments of the plurality of text segments may be compared with one ormore second resources (e.g., an encyclopedia, an online encyclopedia, anews channel, a news website, a website, a book, a research article, aresearch article database and/or a different type of informationdatabase, etc.) to identify the plurality of sets of topics. In someexamples, the one or more first resources (used to identify theplurality of sets of entities) may be the same as the one or more secondresources (used to identify the plurality of sets of topics).Alternatively and/or additionally, the one or more first resources maybe different than the one or more second resources. Alternatively and/oradditionally, the transcript may be analyzed using one or moremulti-label learning (MLL) techniques. For example, text segments may beassigned sets of topics (selected from the list of topics) using the oneor more MLL techniques.

In some examples, the plurality of sets of topics may be identifiedbased upon the plurality of sets of entities. For example, the one ormore MLL techniques may be used to identify and/or select a set oftopics associated with each set of entities of the plurality of sets ofentities. For example, a first set of entities of the plurality ofentities (and/or the first text segment associated with the first set ofentities) may be analyzed using the one or more MLL techniques. A firstset of topics may be selected from the list of topics using the one ormore MLL techniques, based upon the first set of entities (and/or thefirst text segment).

Alternatively and/or additionally, the plurality of sets of entities maybe identified based upon the plurality of sets of topics. For example,text segments of the plurality of text segments may be compared with theone or more first resources to identify the plurality of sets ofentities, based upon the plurality of sets of topics. Alternativelyand/or additionally, the transcript may be analyzed based upon theplurality of sets of topics, using the one or more NER techniques, toidentify the plurality of sets of entities. For example, a second textsegment may be analyzed (using the one or more NER techniques) basedupon a second set of topics (associated with the second text segment) toidentify a second set of entities.

Alternatively and/or additionally, the plurality of sets of topics maybe analyzed to determine contexts (e.g., surrounding substance, generalsubject matter, general labels, etc.) of the plurality of text segments.The plurality of text segments may be compared with the one or morefirst resources to identify the plurality of sets of entities, basedupon the contexts. Alternatively and/or additionally, the transcript maybe analyzed, based upon the contexts, using the one or more NERtechniques, to identify the plurality of sets of entities.

Alternatively and/or additionally, the plurality of sets of entities maybe analyzed to determine contexts (e.g., surrounding substance, generalsubject matter, general labels, etc.) of the plurality of text segments.The plurality of text segments may be compared with the one or moresecond resources to identify the plurality of sets of topics, based uponthe contexts. Alternatively and/or additionally, the transcript may beanalyzed, based upon the contexts, using the one or more NER techniques,to identify the plurality of sets of topics.

In an example, the first text segment (e.g., “The President made a bigdecision today related to jobs”) may be analyzed to identify the firstset of entities associated with the first text segment and/or the firstset of topics associated with the first text segment. For example, thefirst set of entities may comprise a first entity “JamesPresidentsworth” corresponding to a name of a current president, asecond entity “Jun. 1, 2018” corresponding to a date associated with“today” and/or a third entity “job market” corresponding to “jobs”.Alternatively and/or additionally, the first set of topics may comprisea first topic “Politics” and/or a second topic “The Economy” (e.g., thefirst set of topics may be selected from the list of topics). The firstset of topics may be identified based upon the first set of entitiesand/or the first text segment.

Alternatively and/or additionally, the second text segment may comprise:“He announced that construction of numerous highways is being plannedand more job opportunities will be available”. The second text segmentmay be analyzed to identify the second set of entities and/or the secondset of topics. For example, the second set of entities may comprise thefirst entity “James Presidentsworth” corresponding to the name of thecurrent president (e.g., the first entity may be identified based uponthe second text segment comprising “He”, the first text segment and/orthe first set of entities), a fourth entity “highway construction”and/or the third entity “job market” corresponding to “jobopportunities”. Alternatively and/or additionally, the second set oftopics may comprise the first topic “Politics” and/or the second topic“The Economy” (e.g., the second set of topics may be selected from thelist of topics). The second set of topics may be identified based uponthe second set of entities and/or the second text segment.

Alternatively and/or additionally, a third text segment may comprise:“However, the announcement caused backlash by the Speaker of the Housewho said focus needs to be placed on combatting potential flu viruses”.The third text segment may be analyzed to identify a third set ofentities and/or a third set of topics. For example, the third set ofentities may comprise a fifth entity “backlash”, a sixth entity “JuliaSpeakerton” corresponding to a name of a current Speaker of the Houseand/or a seventh entity “flu virus”. Alternatively and/or additionally,the third set of topics may comprise the first topic “Politics” and/or athird topic “Health”. The third set of topics may be identified basedupon the third set of entities and/or the third text segment.

In some examples, the plurality of sets of tags (e.g., the plurality ofsets of entities and/or the plurality of sets of topics) may beidentified based upon the video data (of the first video). For example,rather than (or in addition to) identifying the plurality of sets oftags based upon the transcript (and/or the audio data) the video datamay be analyzed (e.g., using one or more image analysis techniques todetermine people, characters, objects and/or locations associated withthe first video) to identify the plurality of sets of tags.Alternatively and/or additionally, the plurality of sets of tags may beidentified based upon a combination of the transcript and/or the videodata.

In some examples, the plurality of sets of tags (e.g., the plurality ofsets of entities and/or the plurality of sets of topics) may beidentified based upon the determination of a sound track (e.g., of amovie, a television show, a song, a lecture, an audiobook, etc.) basedupon the audio data (of the first video). For example, one or moreportions of the audio data may be determined to match and/or be similarto a sound track in a sound track database (e.g., which may bedetermined based upon a comparison of markers of the audio data andmarkers of the sound track). The name of the sound track, a date of thesound track, entities associated with generating and/or publishing thesound track, and/or entities and/or topics associated with the soundtrack may then be determined and included in the plurality of sets oftags.

In some examples, the plurality of sets of tags (e.g., the plurality ofsets of entities and/or the plurality of sets of topics) may beidentified based upon the recognition of a voice (e.g., of a person, acharacter, etc.) based upon the audio data (of the first video). Forexample, one or more portions of the audio data may be determined tomatch and/or be similar to a defined voice in a voice database (e.g.,which may be determined based upon a comparison of markers of the audiodata and markers of the defined voice). The name associated with thevoice, dates associated with the voice, and/or entities and/or topicsassociated with the voice may then be determined and included in theplurality of sets of tags.

At 408, a plurality of selectable inputs may be generated based upon theplurality of sets of tags. For example, each selectable input of theplurality of selectable inputs may correspond to an indication of a tag(e.g., an entity and/or a topic) of the plurality of sets of tags and atime associated with the tag. For example, each selectable input of theplurality of selectable inputs may comprise an indication of an entityof the plurality of sets of entities and/or an indication of a topic ofthe plurality of sets of topics.

In some examples, each selectable input of the plurality of selectableinputs may comprise an electronic button, a selectable graphical objectand/or a selectable text object. For example, a selectable input of theplurality of selectable inputs may comprise a selectable graphicalobject comprising a selectable image representative of an entity and/ora topic (e.g., a selectable image representative of the currentpresident, a selectable image representative of the economy, etc.).Alternatively and/or additionally, a selectable input of the pluralityof selectable inputs may comprise a selectable text object comprisingselectable text representative of an entity and/or a topic (e.g., “JamesPresidentsworth”, “The Economy”, etc.).

In some examples, each selectable input of the plurality of selectableinputs may be associated with a time (of the first video) associatedwith an entity of the plurality of sets of entities and/or a topic ofthe plurality of sets of topics. Accordingly, the plurality ofselectable inputs may be associated with a plurality of times (of thefirst video). Each selectable input of the plurality of selectableinputs may be associated with a time of the plurality of times. In someexamples, the plurality of times may be (determined) based upon timesegments associated with the plurality of text segments.

For example, a selectable input of the plurality of selectable inputsmay be associated with a time associated with a tag (e.g., an entityand/or a topic). The time (associated with the selectable input) may bedetermined based upon one or more time segments associated with one ormore text segments associated with the tag. For example, the one or moretext segments may be associated with one or more sets of tags comprisingthe tag. Alternatively and/or additionally, the time (associated withthe selectable input) may be determined based upon a text segment(and/or a time segment associated with the text segment) associated withan initial instance of the tag (e.g., a text segment and/or a set oftags comprising the first instance of the tag amongst the plurality oftext segments and/or the plurality of sets of tags). In some examples,the time may correspond to a beginning of the time segment.

In an example, a first selectable input may be generated based upon thefirst entity (e.g., “James Presidentsworth”). The first selectable inputmay comprise a first button, a first selectable graphical object (e.g.,a first selectable image representative of the current president) and/ora first selectable text object (e.g., “James Presidentsworth”, “ThePresident”, “President”, etc.). Alternatively and/or additionally, thefirst selectable input may be associated with a third time. The thirdtime may be determined based upon the first time segment associated withthe first text segment and/or a second time segment associated with thesecond text segment (and/or a different time segment associated with atext segment that is associated with a set of entities comprising thefirst entity). Alternatively and/or additionally, the third time may bedetermined based upon a time segment corresponding to a text segmentassociated with an initial instance of the first entity (e.g., a textsegment and/or a set of entities comprising the first instance of thefirst entity amongst the plurality of text segments and/or the pluralityof sets of entities). Accordingly, responsive to determining that thefirst entity is initially expressed (e.g., expressed for the first time)in the first text segment (e.g., and/or during the first time segment)and/or is comprised within the first set of entities, the third time maybe determined based upon the first time segment (associated with thefirst text segment and/or the first set of entities). In some examples,the third time may correspond to the beginning of the first time segment(e.g., 00:00:03, 3 seconds into the first video, etc.).

In some examples, the plurality of sets of entities may be analyzed togenerate a first plurality of weights associated with the plurality ofsets of entities. For example, each weight of the first plurality ofweights may be assigned to an entity of the plurality of sets ofentities. In some examples, each weight of the first plurality ofweights may be generated and/or assigned to an entity based upon afrequency of the entity in the plurality of sets of entities (e.g., anumber of instances of the entity in the plurality of sets of entities,a number of sets of entities that comprise the entity, etc.).Alternatively and/or additionally, each weight of the first plurality ofweights may be generated and/or assigned to an entity based upon arelevance of the entity in the plurality of sets of entities (e.g., acloseness of subject matter of the entity to other entities of theplurality of sets of entities, a closeness of subject matter of theentity to one or more text segments of the plurality of text segments, acloseness of subject matter of the entity to one or more sets of topicsof the plurality of topics, etc.).

In some examples, the plurality of selectable inputs may comprise asecond plurality of selectable inputs associated with the plurality ofsets of entities. For example, the second plurality of selectable inputsmay comprise indications of entities of the plurality of sets ofentities. Alternatively and/or additionally, the second plurality ofselectable inputs may (merely) comprise indications of a secondplurality of entities assigned a second plurality of weights above afirst weight threshold. For example, the second plurality of selectableinputs may be generated responsive to a determination that each entityof the second plurality of entities (associated with the secondplurality of selectable inputs) is assigned a weight above the firstweight threshold.

Alternatively and/or additionally, the second plurality of selectableinputs may comprise indications of a third plurality of entities,wherein each entity of the third plurality of entities is associatedwith a frequency above a first frequency threshold. For example, thesecond plurality of selectable inputs may be generated responsive to adetermination that each entity of the third plurality of entities(associated with the second plurality of selectable inputs) isassociated with a frequency (e.g., a number of instances of the entityin the plurality of sets of entities, a number of sets of entities thatcomprise the entity, etc.) that is above the first frequency threshold(e.g., a threshold number of instances of an entity in the plurality ofsets of entities, a threshold number of sets of entities that comprisean entity, etc.).

Alternatively and/or additionally, the plurality of sets of entities maybe clustered (and/or grouped) into a plurality of groups of entities.For example, the plurality of sets of entities may be analyzed todetermine the plurality of groups of entities, wherein each group ofentities of the plurality of groups of entities may comprise instancesof the same entity, similar entities, etc. Each group of entities of theplurality of groups of entities may be combined (and/or aggregated) togenerate a fourth plurality of entities. For example, each group ofentities of the plurality of groups of entities may be assigned anentity (e.g., an entity name) based upon the group of entities.Accordingly, each entity of the fourth plurality of entities maycorrespond to a group of entities and/or an entity (e.g., a uniqueentity wherein there are no other entities in the plurality of sets ofentities matching and/or similar to the unique entity).

Thus, the second plurality of selectable inputs may comprise indicationsof the fourth plurality of entities. Alternatively and/or additionally,the second plurality of selectable inputs may comprise indications of(merely) a first portion of the fourth plurality of entities, whereineach entity of the first portion of the fourth plurality of entities isassociated with a weight above the first weight threshold. Alternativelyand/or additionally, the second plurality of selectable inputs maycomprise indications of (merely) a second portion of the fourthplurality of entities, wherein each entity of the second portion of thefourth plurality of entities is associated with a frequency above thefirst frequency threshold (e.g., each entity of the second portion ofthe fourth plurality of entities may correspond to a group of entitiescomprising a number of entities above the first frequency threshold).

In an example, a first weight may be assigned to the first entity (e.g.,“James Presidentsworth”) based upon a first frequency of the firstentity in the plurality of sets of entities (e.g., 46 instances of thefirst entity in the plurality of sets of entities) and/or a firstrelevance of the first entity (e.g., 80% relevance of the first entityto the plurality of sets of entities and/or the plurality of sets oftopics). In some examples, the first weight may be compared with thefirst weight threshold to determine whether to generate the firstselectable input (associated with the first entity). In some examples,the first weight may be above the first weight threshold. Accordingly,the first selectable input may be generated and/or the plurality ofselectable inputs may comprise the first selectable input. Alternativelyand/or additionally, the first weight may be below the first weightthreshold. Accordingly, the first selectable input may not be generatedand/or the plurality of selectable inputs may not comprise the firstselectable input,

Alternatively and/or additionally, the first frequency (e.g., 46), ofthe first entity, may be compared with the first frequency threshold todetermine whether to generate the first selectable input (associatedwith the first entity). In some examples, the first frequency may beabove the first frequency threshold (e.g., the first frequency thresholdmay be 30 and/or a different number less than 46). Accordingly, thefirst selectable input may be generated and/or the plurality ofselectable inputs may comprise the first selectable input. Alternativelyand/or additionally, the first frequency may be below than the firstfrequency threshold (e.g., the first frequency threshold may be 50and/or a different number above 46). Accordingly, the first selectableinput may not be generated and/or the plurality of selectable inputs maynot comprise the first selectable input. Alternatively and/oradditionally, (both) the first weight and the first frequency may becompared with the first weight threshold and the first frequencythreshold to determine whether to generate the first selectable input(associated with the first entity).

In some examples, the plurality of sets of topics may be analyzed togenerate a third plurality of weights associated with the plurality ofsets of topics. For example, each weight of the third plurality ofweights may be assigned to a topic of the plurality of sets of topics.In some examples, each weight of the third plurality of weights may begenerated and/or assigned to a topic based upon a frequency of the topicin the plurality of sets of topics (e.g., a number of instances of thetopic in the plurality of sets of topics, a number of sets of topicsthat comprise the topic, etc.). Alternatively and/or additionally, eachweight of the third plurality of weights may be generated and/orassigned to a topic based upon a relevance of the topic in the pluralityof sets of topics (e.g., a closeness of subject matter of the topic toother topics of the plurality of sets of topics, a closeness of subjectmatter of the topic to one or more text segments of the plurality oftext segments, a closeness of subject matter of the topic to one or moresets of entities, etc.).

In some examples, the plurality of selectable inputs may comprise athird plurality of selectable inputs associated with the plurality ofsets of topics. For example, the third plurality of selectable inputsmay comprise indications of topics of the plurality of sets of topics.Alternatively and/or additionally, the third plurality of selectableinputs may (merely) comprise indications of a second plurality of topicsassigned a fourth plurality of weights above a second weight threshold.For example, the third plurality of selectable inputs may be generatedresponsive to a determination that each topic of the second plurality oftopics (associated with the third plurality of selectable inputs) isassigned a weight above the second weight threshold.

Alternatively and/or additionally, the third plurality of selectableinputs may comprise indications of a third plurality of topics, whereineach topic of the third plurality of topics is associated with afrequency above a second frequency threshold. For example, the thirdplurality of selectable inputs may be generated responsive to adetermination that each topic of the third plurality of topics(associated with the third plurality of selectable inputs) is associatedwith a frequency (e.g., a number of instances of the topic in theplurality of sets of topics, a number of sets of topics that comprisethe topic, etc.) that is above the second frequency threshold (e.g., athreshold number of instances of a topic in the plurality of sets oftopics, a threshold number of sets of topics that comprise a topic,etc.).

Alternatively and/or additionally, the plurality of sets of topics maybe clustered (and/or grouped) into a plurality of groups of topics. Forexample, the plurality of sets of topics may be analyzed to determinethe plurality of groups of topics, wherein each group of topics of theplurality of groups of topics may comprise instances of the same topic,similar topics, etc. Each group of topics of the plurality of groups oftopics may be combined (and/or aggregated) to generate a fourthplurality of topics. For example, each group of topics of the pluralityof groups of topics may be assigned a topic (e.g., a topic name) basedupon the group of topics. Accordingly, each topic of the fourthplurality of topics may correspond to a group of topics and/or a(single) topic (e.g., a unique topic wherein there are no other topicsin the plurality of sets of topics matching and/or similar to the uniquetopic).

Thus, the third plurality of selectable inputs may comprise indicationsof the fourth plurality of topics. Alternatively and/or additionally,the third plurality of selectable inputs may comprise indications of(merely) a first portion of the fourth plurality of topics, wherein eachtopic of the first portion of the fourth plurality of topics isassociated with a weight above the second weight threshold.Alternatively and/or additionally, the third plurality of selectableinputs may comprise indications of (merely) a second portion of thefourth plurality of topics, wherein each topic of the second portion ofthe fourth plurality of topics is associated with a frequency above thesecond frequency threshold (e.g., each topic of the second portion ofthe fourth plurality of topics may correspond to a group of topicscomprising a number of topics above the second frequency threshold).

In some examples, the second plurality of selectable inputs may beformatted based upon the first plurality of weights associated with theplurality of sets of entities (associated with the second plurality ofselectable inputs). For example, a text font, a size, a text color, abackground color, a background pattern, etc. of each selectable input ofthe second plurality of selectable inputs may be formatted based upon aweight (of the first plurality of weights) assigned to an entityassociated with the selectable input. For example, the first selectableinput (associated with the first entity assigned the first weight) maybe formatted having a first format. Alternatively and/or additionally,the second entity may be assigned a second weight. The second weight maybe different than the first weight. Accordingly, a second selectableinput, associated with the second entity, may be generated and/orformatted having a second format, different than the first format. Forexample, the first weight may be greater than the second weight.Accordingly, the first selectable input may have a larger size and/or adarker shade of color than (a size and/or a text color of) the secondselectable input, for example.

Alternatively and/or additionally, the third plurality of selectableinputs may be formatted based upon the third plurality of weightsassociated with the plurality of sets of topics (associated with thethird plurality of selectable inputs). For example, a text font, a size,a text color, a background color, a background pattern, etc. of eachselectable input of the third plurality of selectable inputs may beformatted based upon a weight (of the third plurality of weights)assigned to topic associated with the selectable input. For example, thefirst topic may be assigned a third weight and/or the second topic maybe assigned a fourth weight. The third weight may be different than thefourth weight. Accordingly, a third selectable input, associated withthe first topic, may be generated and/or formatted having a thirdformat. A fourth selectable input, associated with the second topic, maybe generated and/or formatted having a fourth format, different than thethird format. For example, the third weight may be greater than thefourth weight. Accordingly, the third selectable input may have a largersize and/or a darker shade of color than (a size and/or a text color of)the fourth selectable input, for example.

In some examples, the second plurality of selectable inputs (associatedwith the plurality of sets of entities) may be formatted based upon anentity format. For example, a text font, a size, a text color, abackground color, a background pattern, etc. of each selectable input ofthe second plurality of selectable inputs may be generated and/orformatted based upon the entity format. Alternatively and/oradditionally, the third plurality of selectable inputs (associated withthe plurality of sets of topics) may be formatted based upon a topicformat. For example, a text font, a size, a text color, a backgroundcolor, a background pattern, etc. of each selectable input of the thirdplurality of selectable inputs may be generated and/or formatted basedupon the topic format. In some examples, the entity format may bedifferent than the topic format. For example, the second plurality ofselectable inputs may (each) have a first text color (e.g., black, blue,green, red, yellow, etc.) corresponding to the entity format and thethird plurality of selectable inputs may (each) have a second text color(e.g., black, blue, green, red, yellow, etc.) corresponding to the topicformat. The first text color (e.g., blue) may be different than thesecond text color (e.g., red), for example. Alternatively and/oradditionally, the first text color may be the same as the second textcolor.

At 410, the graphical user interface of the device (of the user) may becontrolled to display the video interface comprising the plurality ofselectable inputs. For example, a list of selectable inputs may begenerated, comprising the plurality of selectable inputs. In someexamples, a first portion of the list of selectable inputs may comprisethe second plurality of selectable inputs (associated with the pluralityof sets of entities) and/or a second portion of the list of selectableinputs may comprise the third plurality of selectable inputs (associatedwith the plurality of sets of topics). In some examples, the firstportion of the list of selectable inputs may be separate from the secondportion of the list of selectable inputs. Alternatively and/oradditionally, the first portion of the list of selectable inputs may notbe separate from the second portion of the list of selectable inputs.

In some examples, the list of selectable inputs may be organized, sortedand/or displayed in an order based upon weights associated with theplurality of selectable inputs. For example, selectable inputsassociated with (relatively) greater weights may be displayed before(e.g., above, in front of, etc.) selectable inputs associated with(relatively) lesser weights. In an example, a fifth selectable input maycomprise an indication of a fifth tag (e.g., an entity and/or a topic)having a fifth weight. A sixth selectable input may comprise anindication of a sixth tag (e.g., an entity and/or a topic) having asixth weight. The fifth weight may be greater than the sixth weight.Accordingly, the list of selectable inputs may comprise the fifthselectable input before (e.g., above, in front of, etc.) the sixthselectable input.

Alternatively and/or additionally, the list of selectable inputs may beorganized, sorted and/or displayed in an order based upon timesassociated with the plurality of selectable inputs. For example, theselectable inputs associated with earlier times (of the duration of timeof the first video) may be displayed before (e.g., above, in front of,etc.) selectable inputs associated with later times (of the duration oftime of the first video). In an example, a seventh selectable input maybe associated with a seventh time (e.g., the seventh selectable inputmay comprise an indication of a seventh tag associated with a timesegment corresponding to the seventh time). An eighth selectable inputmay be associated with an eighth time (e.g., the eighth selectable inputmay comprise an indication of an eighth tag associated with a timesegment corresponding to the eighth time). The seventh time may beearlier than the eighth time (e.g., the seventh time may be earlier thanthe eighth time with respect to the duration of time of the firstvideo). Accordingly, the list of selectable inputs may comprise theseventh selectable input before (e.g., above, in front of, etc.) theeighth selectable input.

For example, the list of selectable inputs may be displayed having onecolumn comprising the plurality of selectable inputs. Alternativelyand/or additionally, the list of selectable inputs may be displayedhaving a first set of columns comprising the first portion of the listof selectable inputs (corresponding to the second plurality ofselectable inputs associated with the plurality of sets of entities) anda second set of columns comprising the second portion of the list ofselectable inputs (corresponding to the third plurality of selectableinputs associated with the plurality of sets of topics).

Alternatively and/or additionally, the list of selectable inputs may bedisplayed having a shape. For example, the list of selectable inputs maybe displayed within a square-shaped outline. The square-shaped outlinemay be displayed, surrounding the list of selectable inputs (e.g., asquare-shaped border surrounding the list of selectable inputs may bedisplayed). Alternatively and/or additionally, the square-shaped outlinemay not be displayed (e.g., there may not be a border surrounding thelist of selectable inputs). For example, the list of selectable inputsmay resemble a square-like shape.

Alternatively and/or additionally, the list of selectable inputs may bedisplayed within a rectangular outline. For example, the list ofselectable inputs may be displayed within a rectangular outline. Therectangular outline may be displayed, surrounding the list of selectableinputs (e.g., a rectangular border surrounding the list of selectableinputs may be displayed). Alternatively and/or additionally, therectangular outline may not be displayed (e.g., there may not be aborder surrounding the list of selectable inputs). For example, the listof selectable inputs may resemble a rectangular shape.

Alternatively and/or additionally, the list of selectable inputs may bedisplayed within a circular outline. The circular outline may bedisplayed, surrounding the list of selectable inputs (e.g., a circularborder surrounding the list of selectable inputs may be displayed).Alternatively and/or additionally, the circular outline may not bedisplayed (e.g., there may not be a border surrounding the list ofselectable inputs). For example, the list of selectable inputs mayresemble a circular shape.

Alternatively and/or additionally, the list of selectable inputs may bedisplayed within an elliptical outline (e.g., a cloud-shaped outline, abubble-shaped outline, etc.). The elliptical outline may be displayed,surrounding the list of selectable inputs (e.g., an elliptical border, acloud-like border and/or a bubble-like border surrounding the list ofselectable inputs may be displayed). Alternatively and/or additionally,the elliptical outline may not be displayed (e.g., there may not be aborder surrounding the list of selectable inputs). For example, the listof selectable inputs may resemble an elliptical shape (e.g., acloud-like shape, a bubble-like shape, etc.).

In some examples, the graphical user interface of the device may becontrolled to display the list of selectable inputs (comprising theplurality of selectable inputs) responsive to (receiving) a selection ofthe first video. For example, the list of videos of the video interfacemay comprise a fourth plurality of selectable inputs corresponding to asecond plurality of videos. In some examples, a ninth selectable inputof the fourth plurality of selectable inputs (of the list of videos) maybe associated with the first video.

For example, responsive to (receiving) a selection of the ninthselectable input, the list of selectable inputs (associated with theplurality of sets of tags of the first video) may be displayed.Alternatively and/or additionally, the first video may be displayedadjacent to the list of selectable inputs (e.g., the first video may bedisplayed above, below, next to, etc. the list of selectable inputs).

At 412, a selection of a tenth selectable input of the plurality ofselectable inputs may be received via the video interface (and/or thelist of selectable inputs). In some examples, the tenth selectable inputmay be associated with a tenth tag (e.g., an entity and/or a topic) ofthe plurality of sets of tags and/or a tenth time of the first video.For example, the tenth selectable input may comprise an indication ofthe tenth tag and/or the tenth tag may be associated with a time segmentassociated with the tenth time.

At 414, responsive to receiving the selection of the tenth selectableinput, a second graphical user interface of a second device may becontrolled to display the first video. The first video may be displayedbased upon the tenth time of the first video. For example, the firstvideo may be displayed beginning with (e.g., starting at) the tenth timeof the duration of time of the first video. Alternatively and/oradditionally, the first video may be displayed beginning with (e.g.,starting at) a third duration of time (e.g., a few seconds, 10 seconds,1 minute, etc.) before the tenth time (of the duration of time) of thefirst video (such that a context of the tenth time may be conveyed tothe user and/or one or more viewers of the first video).

In some examples, the second device may be the same as the first deviceand/or the second graphical user interface may be the same as the firstgraphical user interface. In an example, the first device (and/or thesecond device) may comprise a television (e.g., a smart television), aphone (e.g., a smart phone), a tablet, a computer (e.g., a desktopcomputer, a laptop, a computer connected to a television and/or amonitor, etc.), etc.

Alternatively and/or additionally, the second device may be differentthan the first device and/or the second graphical user interface may bedifferent than the first graphical user interface. For example, one ormore videos may be selected from the list of videos (via the videointerface) using the first device (e.g., a smart phone, a computer, atablet, etc.) and/or the one or more videos may be displayed using thesecond device (e.g., a television, a computer connected to a televisionand/or a monitor, etc.). For example, the second device may be connectedto the first device via a network connection (e.g., WiFi, Bluetooth,etc.).

FIGS. 5A-5E illustrate examples of a system 501 for displaying videosbased upon selectable inputs associated with tags. A first user, such asuser James (and/or a first device 500 associated with the first user)may access and/or interact with a service, such as a website, anapplication, etc. that provides a platform for viewing and/ordownloading videos from one or more servers (of the website, theapplication, etc.). For example, a first graphical user interface of thefirst device may be controlled to display a video interface. In someexamples, the video interface may enable the first user and/or the firstdevice to upload content (e.g., videos, images, etc.) to the one or moreservers.

FIG. 5A illustrates the first graphical user interface of the firstdevice 500 being controlled to display the video interface. The firstdevice 500 may comprise a button 502, a microphone 504 and/or a speaker506. For example, the video interface may display instructions 508and/or a first selectable input 510 corresponding to uploading one ormore videos to the one or more servers and/or to a video databaseassociated with the service. In some examples, responsive to a selectionof the first selectable input 510, a first video may be selected and/oruploaded to the one or more servers.

FIG. 5B illustrates a backend system 525 (e.g., on the one or moreservers of the service and/or on the first device 525 of the first user)that may generate a plurality of selectable inputs 542 (associated withthe first video) responsive to the first video being uploaded to the oneor more servers and/or to the video database. In some examples, thefirst video and/or a set of information 516 associated with the firstvideo may be identified. The set of information 516 may comprise a titleof the video “OUR INTERNATIONAL TRIP” and/or a duration of time of thefirst video “00:10:38” (e.g., the duration of time of the first videomay be 10 minutes and 38 seconds).

The first video may comprise video data and/or audio data. A transcript518 may be determined associated with the audio data of the first video.In some examples, the transcript 518 may be retrieved from the set ofinformation 516 and/or the transcript 518 may be retrieved from thefirst video (e.g., the first video may comprise the transcript 518).Alternatively and/or additionally, the audio data may be transcribed togenerate the transcript 518.

In some examples, the transcript 518 may comprise a plurality of textsegments. In some examples, the transcript 518 may comprise a set ofcaptions and/or a set of subtitles associated with the first video. Forexample, each text segment of the plurality of text segments maycomprise a caption of the set of captions and/or a subtitle of the setof subtitles. Each text segment of the plurality of text segments may beassociated with a time segment of the duration of time of the firstvideo. For example, a first text segment “We began our journey inAfrica” may be associated with a first time segment “00:00:04→00:00:12”indicating that the first text segment corresponds to words and/orsounds of the audio data from a first time of the first video (e.g.,00:00:004, 4 seconds into the first video, etc.) to a second time of thefirst video (e.g., 00:00:12, 12 seconds into the first video, etc.).

The transcript 518 may be analyzed to identify a plurality of sets oftags. For example, the plurality of sets of tags may compriseindications of a plurality of sets of entities 520 and/or a plurality ofsets of topics 522. For example, the plurality of sets of entities 520(e.g., named entities) may comprise subjects (expressed, discussed,etc.) in the first video. In some examples, the transcript 518 may beanalyzed (using one or more NER techniques and/or other techniques) toidentify the plurality of sets of entities 520. Each set of entities ofthe plurality of sets of entities 520 may correspond to a text segmentof the plurality of text segments (of the transcript 518). For example,the first text segment (e.g., “We began our journey in Africa”) may beanalyzed to identify a first set of entities (of the plurality of setsof entities 520) associated with the first text segment. For example,the first set of entities may comprise a first entity “Journey” and/or asecond entity “Africa”.

Alternatively and/or additionally, the plurality of sets of topics 522(e.g., labels) may comprise topics (expressed, discussed, etc.) in thefirst video. In some examples, the transcript 518 may be analyzed (usingone or more MLL techniques and/or other techniques) to identify theplurality of sets of topics 522. In some examples, the plurality of setsof topics may (each) be selected from a list of topics. For example, thelist of topics may be based upon the subject matter of the first video.For example, it may be determined that the first video is associatedwith travel (based upon the set of information 516, based upon thetranscript 518, based upon user-defined information, etc.). Accordingly,the list of topics may comprise: Travel destinations, Cuisine,Transportation, Cost-friendliness, Asia Tourism, South America Tourism,Africa Tourism, etc.

Each set of topics of the plurality of sets of topics 522 may correspondto a text segment of the plurality of text segments (of the transcript518). For example, the first text segment (e.g., “We began our journeyin Africa”) may be analyzed to identify a first set of topics (of theplurality of sets of topics 522) associated with the first text segment.For example, the first set of topics may comprise a first topic “AfricaTourism.”

In some examples, the plurality of sets of entities 520 and/or thetranscript 518 may be analyzed to generate a first plurality of weightsassociated with the plurality of sets of entities 520. For example, thefirst plurality of weights may be generated based upon a frequency, arelevance, etc. of entities of the plurality of sets of entities 520.Alternatively and/or additionally, the plurality of sets of topics 522and/or the transcript 518 may be analyzed to generate a second pluralityof weights associated with the plurality of sets of topics 522. Forexample, the second plurality of weights may be generated based upon afrequency, a relevance, etc. of topics of the plurality of sets oftopics 522.

The plurality of selectable inputs 542 may be generated based upon theplurality of sets of entities 520, the first plurality of weights, theplurality of sets of topics 522 and/or the second plurality of weights.In some examples, the plurality of selectable inputs 542 may comprise asecond plurality of selectable inputs associated with the plurality ofsets of entities 520. For example, the second plurality of selectableinputs may comprise indications of entities of the plurality of sets ofentities 520. Alternatively and/or additionally, the plurality ofselectable inputs 542 may comprise a third plurality of selectableinputs associated with the plurality of sets of topics 522. For example,the third plurality of selectable inputs may comprise indications oftopics of the plurality of sets of topics 522.

FIG. 5C illustrates a second graphical user interface of a second device550 (associated with a second user, such as user Janet) being controlledto display the video interface comprising a list of videos. In someexamples, the video interface may display an input search area 528 forsearching for videos (of the video database). For example, the list ofvideos may comprise a second selectable input 530 associated with asecond video of the video database, a third selectable input 532associated with the first video and/or a fourth selectable input 534associated with a third video of the video database. For example, aselection of the third selectable input 532 may be received (from thesecond device 550). In some examples, responsive to the selection of thethird selectable input 532, the video interface may display the firstvideo and/or the plurality of selectable inputs 542.

FIG. 5D illustrates the second graphical user interface of the seconddevice 550 being controlled to display the first video and/or theplurality of selectable inputs 542. In some examples, the videointerface may display a time indication 540 adjacent to (e.g., below)the first video. For example, the time indication 540 may indicate atime of (the duration of time of) the first video that is beingpresented.

In some examples, the second plurality of selectable inputs (associatedwith the plurality of sets of entities 520) may be formatted based uponthe first plurality of weights associated with the plurality of sets ofentities 520. For example, a text font, a size, a text color, abackground color, a background pattern, etc. of each selectable input ofthe second plurality of selectable inputs may be formatted based upon aweight assigned to an entity associated with the selectable input. Forexample, the second plurality of selectable inputs may comprise a fifthselectable input 544 associated with a third entity “Deserts” assigned afirst weight. Alternatively and/or additionally, the second plurality ofselectable inputs may comprise a sixth selectable input 546 associatedwith the second entity (e.g., “Africa”) assigned a second weight. Insome examples, the second weight may be greater than the first weight.Accordingly, the sixth selectable input 546 may have a larger size than(a size of) the fifth selectable input 544, for example.

Alternatively and/or additionally, the third plurality of selectableinputs (associated with the plurality of sets of topics 522) may beformatted based upon the second plurality of weights associated with theplurality of sets of topics 522. For example, a text font, a size, atext color, a background color, a background pattern, etc. of eachselectable input of the third plurality of selectable inputs may beformatted based upon a weight assigned to a topic associated with theselectable input. For example, the third plurality of selectable inputsmay comprise a seventh selectable input 548 associated with a secondtopic “Visual Arts” assigned a third weight. Alternatively and/oradditionally, the third plurality of selectable inputs may comprise aneighth selectable input 550 associated with a third topic “Cuisine”assigned a fourth weight. In some examples, the fourth weight may begreater than the third weight. Accordingly, the eighth selectable input550 may have a larger size than a size of the seventh selectable input548, for example.

Alternatively and/or additionally, the second plurality of selectableinputs (associated with the plurality of sets of entities 520) may beformatted based upon an entity format. Alternatively and/oradditionally, the third plurality of selectable inputs (associated withthe plurality of sets of topics 522) may be formatted based upon a topicformat. In some examples, the entity format may be different than thetopic format. For example, the second plurality of selectable inputs may(each) have a first font, a first text color and/or a first shadecorresponding to the entity format and the third plurality of selectableinputs may (each) have a second font, a second text color and/or asecond shade corresponding to the topic format. The first font (e.g.,underlined) may be different than the second font (e.g., bold).Alternatively and/or additionally, the first text color (and/or thefirst shade) may be different than the second text color (and/or thesecond shade).

In some examples, a selection of the fifth selectable input 544 may bereceived. In some examples, the fifth selectable input 544 may beassociated with a third time of (the duration of time of) the firstvideo. For example, the third entity (e.g., “Deserts) (associated withthe fifth selectable input 544) may be associated with a second timesegment “00:03:42→00:03:54”. For example, the third entity may beassociated with a second text segment associated with the second timesegment. Accordingly, the third time of the first video may be abeginning of the second time segment (e.g., “00:03:42”, 3 minutes and 42seconds into the first video, etc.). Alternatively and/or additionally,the third time of the first video may be a second duration of time priorto the beginning of the second time segment.

FIG. 5E illustrates the second graphical user interface of the seconddevice 550 being controlled to display the first video based upon thethird time of the first video. For example, the second graphical userinterface of the second device 550 may be controlled to display thefirst video based upon the third time responsive to (receiving) theselection of the fifth selectable input 544. The first video may bedisplayed beginning with (e.g., starting at) the third time.

It may be appreciated that the disclosed subject matter may assist auser (and/or a device associated with the user) in displaying videosbased upon selectable inputs associated with tags. Alternatively and/oradditionally, the disclosed subject matter may assist the user (and/orthe device) in displaying one or more segments of a video associatedwith subject matter (e.g., topics and/or entities) that may be ofinterest to the user.

Implementation of at least some of the disclosed subject matter may leadto benefits including, but not limited to, a reduction in screen spaceand/or an improved usability of a display (e.g., of the device) (e.g.,as a result of enabling the device to display a plurality of selectableinputs corresponding to a plurality of tags, as a result of enabling thedevice and/or the user to select a selectable input associated withsubject matter of interest to the user, as a result of presenting thevideo based upon a time associated with the selectable input, whereinthe user and/or the device may not need to navigate through parts of thevideo in order to find the time associated with the subject matter,wherein a separate application and/or a separate window may not need tobe opened in order to search for the time associated with the subjectmatter, etc.).

Alternatively and/or additionally, implementation of at least some ofthe disclosed subject matter may lead to benefits including increasingan accuracy and/or precision in transmitting requested and/or desiredcontent to the device and/or presenting the requested and/or desiredcontent to the user (e.g., as a result of enabling the device and/or theuser to select the selectable input associated with the subject matterof interest to the user, as a result of presenting the video based uponthe time associated with the selectable input and/or the subject matter,etc.).

Alternatively and/or additionally, implementation of at least some ofthe disclosed subject matter may lead to benefits including a reductionin bandwidth (e.g., as a result of reducing a need for navigatingthrough parts of the video and/or downloading the parts of the video inan effort to find the time associated with the subject matter, etc.).

In some examples, at least some of the disclosed subject matter may beimplemented on a device (e.g., a client device), and in some examples,at least some of the disclosed subject matter may be implemented on aserver (e.g., hosting a service accessible via a network, such as theInternet).

FIG. 6 is an illustration of a scenario 600 involving an examplenon-transitory machine readable medium 602. The non-transitory machinereadable medium 602 may comprise processor-executable instructions 612that when executed by a processor 616 cause performance (e.g., by theprocessor 616) of at least some of the provisions herein (e.g.,embodiment 614). The non-transitory machine readable medium 602 maycomprise a memory semiconductor (e.g., a semiconductor utilizing staticrandom access memory (SRAM), dynamic random access memory (DRAM), and/orsynchronous dynamic random access memory (SDRAM) technologies), aplatter of a hard disk drive, a flash memory device, or a magnetic oroptical disc (such as a compact disc (CD), digital versatile disc (DVD),or floppy disk). The example non-transitory machine readable medium 602stores computer-readable data 604 that, when subjected to reading 606 bya reader 610 of a device 608 (e.g., a read head of a hard disk drive, ora read operation invoked on a solid-state storage device), express theprocessor-executable instructions 612. In some embodiments, theprocessor-executable instructions 612, when executed, cause performanceof operations, such as at least some of the example method 400 of FIG.4, for example. In some embodiments, the processor-executableinstructions 612 are configured to cause implementation of a system,such as at least some of the example system 501 of FIGS. 5A-5E, forexample.

3. Usage of Terms

As used in this application, “component,” “module,” “system”,“interface”, and/or the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a controller and the controller can be a component. One or morecomponents may reside within a process and/or thread of execution and acomponent may be localized on one computer and/or distributed betweentwo or more computers.

Unless specified otherwise, “first,” “second,” and/or the like are notintended to imply a temporal aspect, a spatial aspect, an ordering, etc.Rather, such terms are merely used as identifiers, names, etc. forfeatures, elements, items, etc. For example, a first object and a secondobject generally correspond to object A and object B or two different ortwo identical objects or the same object.

Moreover, “example” is used herein to mean serving as an instance,illustration, etc., and not necessarily as advantageous. As used herein,“or” is intended to mean an inclusive “or” rather than an exclusive“or”. In addition, “a” and “an” as used in this application aregenerally be construed to mean “one or more” unless specified otherwiseor clear from context to be directed to a singular form. Also, at leastone of A and B and/or the like generally means A or B or both A and B.Furthermore, to the extent that “includes”, “having”, “has”, “with”,and/or variants thereof are used in either the detailed description orthe claims, such terms are intended to be inclusive in a manner similarto the term “comprising”.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing at least some of the claims.

Furthermore, the claimed subject matter may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. Of course, manymodifications may be made to this configuration without departing fromthe scope or spirit of the claimed subject matter.

Various operations of embodiments are provided herein. In an embodiment,one or more of the operations described may constitute computer readableinstructions stored on one or more computer and/or machine readablemedia, which if executed will cause the operations to be performed. Theorder in which some or all of the operations are described should not beconstrued as to imply that these operations are necessarily orderdependent. Alternative ordering will be appreciated by one skilled inthe art having the benefit of this description. Further, it will beunderstood that not all operations are necessarily present in eachembodiment provided herein. Also, it will be understood that not alloperations are necessary in some embodiments.

Also, although the disclosure has been shown and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure. In addition, while aparticular feature of the disclosure may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.

What is claimed is:
 1. A method, comprising: identifying a video,wherein the video comprises video data and audio data; determining atranscript associated with the audio data, wherein the transcriptcomprises a plurality of text segments, wherein each text segment of theplurality of text segments is associated with a time segment of aduration of time of the video; analyzing the transcript to generate aplurality of sets of tags associated with the transcript, wherein eachset of tags of the plurality of sets of tags corresponds to a textsegment of the plurality of text segments; generating a plurality ofselectable inputs based upon the plurality of sets of tags, wherein eachselectable input of the plurality of selectable inputs comprises textrepresentative of a tag of the plurality of sets of tags and a timeassociated with the tag, wherein a first selectable input of theplurality of selectable inputs comprises first text, comprising a firstword, representative of a first tag associated with a first time of thevideo and a second selectable input of the plurality of selectableinputs comprises second text, comprising a second word, representativeof a second tag associated with a second time of the video; displaying avideo interface comprising the plurality of selectable inputs; receivinga selection of the first selectable input of the plurality of selectableinputs via the video interface; and responsive to receiving theselection of the first selectable input associated with the first tag,modifying the video interface to display the video based upon the firsttime associated with the first selectable input.
 2. The method of claim1, wherein: the second tag is different than the first tag; theanalyzing the transcript comprises identifying a plurality of sets ofentities, wherein each set of entities of the plurality of sets ofentities corresponds to a text segment of the plurality of textsegments; and the plurality of sets of tags comprises indications of theplurality of sets of entities, the method comprising: analyzing theplurality of sets of entities to generate a first plurality of weightsassociated with the plurality of sets of entities, wherein each weightof the first plurality of weights is assigned to an entity of theplurality of sets of entities based upon a frequency of the entity inthe plurality of sets of entities.
 3. The method of claim 1, wherein:the second tag is different than the first tag; the analyzing thetranscript comprises identifying a plurality of sets of topics, whereineach set of topics of the plurality of sets of topics corresponds to atext segment of the plurality of text segments; and the plurality ofsets of tags comprises indications of the plurality of sets of topics,the method comprising: analyzing the plurality of sets of topics togenerate a first plurality of weights associated with the plurality ofsets of topics, wherein each weight of the first plurality of weights isassigned to a topic of the plurality of sets of topics based upon afrequency of the topic in the plurality of sets of topics.
 4. The methodof claim 1, wherein the displaying the video interface comprising theplurality of selectable inputs comprises: displaying the firstselectable input in a first position in the video interface based uponthe first tag; and displaying the second selectable input in a secondposition in the video interface based upon the second tag.
 5. The methodof claim 1, wherein the displaying the video interface comprising theplurality of selectable inputs comprises: displaying the firstselectable input in a first position in the video interface based upon afirst weight associated with the first selectable input; and displayingthe second selectable input in a second position in the video interfacebased upon a second weight associated with the second selectable input.6. The method of claim 1, wherein: the analyzing the transcriptcomprises identifying a plurality of sets of topics, wherein each set oftopics of the plurality of sets of topics corresponds to a text segmentof the plurality of text segments; and the plurality of sets of tagscomprises indications of the plurality of sets of topics.
 7. The methodof claim 6, comprising: analyzing the plurality of sets of topics togenerate a second plurality of weights associated with the plurality ofsets of topics, wherein each weight of the second plurality of weightsis assigned to a topic of the plurality of sets of topics based upon afrequency of the topic in the plurality of sets of topics.
 8. The methodof claim 7, wherein: the plurality of selectable inputs comprises athird plurality of selectable inputs associated with the plurality ofsets of topics; and the generating the plurality of selectable inputscomprises formatting each selectable input of the third plurality ofselectable inputs based upon a weight assigned to a topic of theplurality of sets of topics associated with the selectable input.
 9. Themethod of claim 1, wherein: the analyzing the transcript comprises:identifying a plurality of sets of entities, wherein each set ofentities of the plurality of sets of entities corresponds to a textsegment of the plurality of text segments; and identifying a pluralityof sets of topics, wherein each set of topics of the plurality of setsof topics corresponds to a text segment of the plurality of textsegments; the plurality of sets of tags comprises indications of theplurality of sets of entities and indications of the plurality of setsof topics; the plurality of selectable inputs comprises a secondplurality of selectable inputs associated with the plurality of sets ofentities and a third plurality of selectable inputs associated with theplurality of sets of topics; the generating the plurality of selectableinputs comprises formatting each selectable input of the secondplurality of selectable inputs based upon a first format; the generatingthe plurality of selectable inputs comprises formatting each selectableinput of the third plurality of selectable inputs based upon a secondformat; and the first format is different than the second format. 10.The method of claim 9, wherein the identifying the plurality of sets ofentities is performed based upon the plurality of sets of topics. 11.The method of claim 9, wherein the identifying the plurality of sets oftopics is performed based upon the plurality of sets of entities. 12.The method of claim 1, wherein the first selectable input has adifferent format than the second selectable input.
 13. The method ofclaim 1, wherein the first text represents at least one of a firstentity or a first topic and the second text represents at least one of asecond entity or a second topic.
 14. A computing device comprising: aprocessor; and memory comprising processor-executable instructions thatwhen executed by the processor cause performance of operations, theoperations comprising: generating a plurality of selectable inputs basedupon a plurality of sets of tags associated with a video, wherein eachselectable input of the plurality of selectable inputs corresponds to anindication of a tag of the plurality of sets of tags and a timeassociated with the tag; displaying a video interface comprising theplurality of selectable inputs; receiving a selection of a firstselectable input of the plurality of selectable inputs via the videointerface, wherein the first selectable input is associated with a firsttag of the plurality of sets of tags and a first time of the video; andresponsive to receiving the selection of the first selectable inputassociated with the first tag, modifying the video interface to displaythe video based upon the first time associated with the first selectableinput, wherein at least one of: the first selectable input of theplurality of selectable inputs comprises first text representative ofthe first tag and a second selectable input of the plurality ofselectable inputs comprises second text representative of a second tag;the displaying comprises displaying the first selectable input with adifferent format than the second selectable input; the displaying thevideo interface comprising the plurality of selectable inputs comprises:displaying the first selectable input in a first position in the videointerface based upon the first tag; and displaying the second selectableinput in a second position in the video interface based upon the secondtag; or the displaying the video interface comprising the plurality ofselectable inputs comprises: displaying the first selectable input inthe first position in the video interface based upon a first weightassociated with the first selectable input; and displaying the secondselectable input in the second position in the video interface basedupon a second weight associated with the second selectable input. 15.The computing device of claim 14, wherein the first tag is differentthan the second tag of the plurality of sets of tags.
 16. The computingdevice of claim 15, wherein the first time is different than a secondtime associated with the second tag.
 17. A non-transitory machinereadable medium having stored thereon processor-executable instructionsthat when executed cause performance of operations, the operationscomprising: identifying a video, wherein the video comprises video dataand audio data; determining a transcript associated with the audio data,wherein the transcript comprises a plurality of text segments, whereineach text segment of the plurality of text segments is associated with atime segment of a duration of time of the video; analyzing thetranscript to generate a plurality of sets of tags associated with thetranscript, wherein each set of tags of the plurality of sets of tagscorresponds to a text segment of the plurality of text segments; andgenerating a plurality of selectable inputs based upon the plurality ofsets of tags, wherein each selectable input of the plurality ofselectable inputs corresponds to an indication of a tag of the pluralityof sets of tags and a time associated with the tag, wherein a firstselectable input of the plurality of selectable inputs corresponds to anindication of a first tag associated with a first time of the video anda second selectable input of the plurality of selectable inputscorresponds to an indication of a second tag associated with a secondtime of the video, wherein at least one of: the first selectable inputcomprises first text representative of the first tag and the secondselectable input comprises second text representative of the second tag;or the first selectable input has a different format than the secondselectable input.
 18. The non-transitory machine readable medium ofclaim 17, wherein: the analyzing the transcript comprises: identifying aplurality of sets of entities, wherein each set of entities of theplurality of sets of entities corresponds to a text segment of theplurality of text segments; and identifying a plurality of sets oftopics, wherein each set of topics of the plurality of sets of topicscorresponds to a text segment of the plurality of text segments; theplurality of sets of tags comprises indications of the plurality of setsof entities and indications of the plurality of sets of topics; theplurality of selectable inputs comprises a second plurality ofselectable inputs associated with the plurality of sets of entities anda third plurality of selectable inputs associated with the plurality ofsets of topics; the generating the plurality of selectable inputscomprises formatting each selectable input of the second plurality ofselectable inputs based upon a first format; the generating theplurality of selectable inputs comprises formatting each selectableinput of the third plurality of selectable inputs based upon a secondformat; and the first format is different than the second format. 19.The non-transitory machine readable medium of claim 18, wherein theidentifying the plurality of sets of entities is performed based uponthe plurality of sets of topics.
 20. The non-transitory machine readablemedium of claim 18, wherein the identifying the plurality of sets oftopics is performed based upon the plurality of sets of entities.